{"id":"W6948816564","doi":"10.5281/zenodo.10851779","title":"RISK MANAGEMENT USING DATA SCIENCE APPROACHES","year":2024,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"activated carbon and charcoal","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bell (Canada)","funders":"","keywords":"Risk management; Big data; Adaptability; Visibility; Flexibility (engineering); Reputation; Risk assessment; Function (biology); Analytics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.005655123,0.0001180332,0.0001155368,0.0006683019,0.002527306,0.004709682,0.004704141,0.00003589198,0.0059937],"category_scores_gemma":[0.001435969,0.00009727392,0.0000387035,0.002750063,0.0004885514,0.001307599,0.005774661,0.0002812318,0.009145563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001545848,"about_ca_system_score_gemma":0.00001058096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001018729,"about_ca_topic_score_gemma":1.249439e-7,"domain_scores_codex":[0.9964018,0.0003115862,0.0003000376,0.0009971284,0.001608889,0.000380537],"domain_scores_gemma":[0.9979147,0.0000547986,0.0000825343,0.001461556,0.0002972774,0.0001891891],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002538585,0.00007872611,0.000006768647,0.00002656768,0.00005032964,0.00004614855,0.001126347,0.0002026143,0.001835017,0.03714663,0.1501194,0.8093361],"study_design_scores_gemma":[0.0001140943,0.00003532438,0.0001622819,0.00002071891,0.00001790448,0.00006993479,0.001617412,0.07650638,0.0002795586,0.002059447,0.9189858,0.0001311853],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03563305,0.0004474912,0.06387797,0.0010824,0.0006623967,0.0006011217,0.0006425695,0.001512735,0.8955402],"genre_scores_gemma":[0.9966246,0.00007109295,0.001178371,0.00004846894,0.0001407092,1.049084e-8,0.00021581,0.0004920511,0.001228882],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9609916,"threshold_uncertainty_score":0.9987713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3600500339285415,"score_gpt":0.3752541648197278,"score_spread":0.01520413089118633,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}